Robust modelling of noisy ARMA signals

In this paper methods are developed for enhancement and analysis of autoregressive moving average (ARMA) signals observed in additive noise which can be represented as mixtures of heavy-tailed non-Gaussian sources and a Gaussian background component. Such models find application in systems such as atmospheric communications channels or early sound recordings which are prone to intermittent impulse noise. Markov Chain Monte Carlo (MCMC) simulation techniques are applied to the joint problem of signal extraction, model parameter estimation and detection of impulses within a fully Bayesian framework. The algorithms require only simple linear iterations for all of the unknowns, including the MA parameters, which is in contrast with existing MCMC methods for analysis of noise-free ARMA models. The methods are illustrated using synthetic data and noise-degraded sound recordings.

Microstructural modelling in friction stir welding of 2000 series aluminium alloys

Simple process models are applied to predict microstructural changes due to the thermal cycle imposed in friction stir welding. A softening model developed for heat-treatable aluminium alloys of the 6000 series is applied to the aerospace alloy 2014 in the peak-aged (T6) condition. It is found that the model is not readily applicable to alloy 2024 in the naturally aged (T3) temper, but the softening behaviour can still be described semi-empirically. Both analytical and numerical (finite element) thermal models are used to predict the thermal histories in trial welds. These are coupled to the microstructural model to investigate: (a) the hardness profile across the welded plate; (b) alloy softening ahead of the approaching welding tool. By incorporating the softening model applied to 6082-T6 alloy, the hardness profile of friction stir welds in dissimilar alloys is also predicted. © AFM, EDP Sciences 2005.

Modelling soot formation in a DISI engine

In this work, the formation of soot in a Direct Injection Spark Ignition (DISI) engine is simulated using the Stochastic Reactor Model (SRM) engine code. Volume change, convective heat transfer, turbulent mixing, direct injection and flame propagation are accounted for. In order to simulate flame propagation, the cylinder is divided into an unburned, entrained and burned zone, with the rate of entrainment being governed by empirical equations but combustion modelled with chemical kinetics. The model contains a detailed chemical mechanism as well as a highly detailed soot formation model, however computation times are relatively short. The soot model provides information on the morphology and chemical composition of soot aggregates along with bulk quantities, including soot mass, number density, volume fraction and surface area. The model is first calibrated by simulating experimental data from a Gasoline Direct Injection (GDI) Spark Ignition (SI) engine. The model is then used to simulate experimental data from the literature, where the numbers, sizes and derived mass particulate emissions from a 1.83 L, 4-cylinder, 4 valve production DISI engine were examined. Experimental results from different injection and spark timings are compared with the model and the qualitative trends in aggregate size distribution and emissions match the exhaust gas measurements well. © 2010 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

The design of an agent for modelling supply chain network dynamics

A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.

Kinetics of the chemical looping oxidation of H2 by a co-precipitated mixture of CuO and Al2O3

Chemical-looping combustion (CLC) has the inherent property of separating CO2 from flue gases. Instead of air, it uses an oxygen-carrier, usually in the form of a metal oxide, to provide oxygen for combustion. When used for the combustion of gaseous fuels, such as natural gas, or synthesis gas from the gasification of coal, the technique gives a stream of CO2 which, on an industrial scale, would be sufficiently pure for geological sequestration. An important issue is the form of the metal oxide, since it must retain its reactivity through many cycles of complete reduction and oxidation. Here, we report on the rates of oxidation of one constituent of synthesis gas, H2, by co-precipitated mixtures of CuO+Al2O3 using a laboratory-scale fluidised bed. To minimise the influence of external mass transfer, and also of errors in the measurement of [H2], particles sized to 355-500μm were used at low [H2], with the temperature ranging from 450 to 900°C. Under such conditions, the reaction was slow enough for meaningful measurements of the intrinsic kinetics to be made. The reaction was found to be first order with respect to H2. Above ∼800°C, the reaction of CuO was fast and conformed to the shrinking core mechanism, proceeding via the intermediate, Cu2O, in: 2CuO+H2→Cu2O+H2O, ΔH1073 K0=- 116.8 kJ/mol; Cu2O+H2→2Cu+H2O, ΔH1073 K0-80.9 kJ/mol. After oxidation of the products Cu and Cu2O back to CuO, the kinetics in subsequent cycles of chemical looping oxidation of H2 could be approximated by those in the first. Interestingly, the carrier was found to react at temperatures as low as 300°C. The influence of the number of cycles of reduction and oxidation is explored. Comparisons are drawn with previous work using reduction by CO. Finally, these results indicate that the kinetics of reaction of the oxygen carrier with gasifier synthesis gases is very much faster than rates of gasification of the original fuel. © 2010 The Institution of Chemical Engineers.

Modelling of Laminar Plasma Jet Impinging on a Flatplate with Approximate Box Relaxation Method

Approximate Box Relaxation method was used t'o simulate a plasma jet flow impinging on a flatplate at atmospheric pressure, to achieve a better understanding of the characteristics of plasma jet in materials surface treating. The flow fields under different conditions were simulated and analyzed. The distributions of temperature, velocity and pressure were obtained by modelling. Computed results indicate that this numerical method is suitable for simulation of the flow characteristics of plasma jet: and is helpful for understanding of the mechanism of the plasma-material processing.